Predictive Modelling for Incremental Cold Flow Forming: An integrated framework for fundamental understanding and process optimisation
增量冷流成型的预测建模:用于基本理解和流程优化的集成框架
基本信息
- 批准号:EP/T008415/1
- 负责人:
- 金额:$ 157.15万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2020
- 资助国家:英国
- 起止时间:2020 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Incremental cold flow forming (ICFF) is a metal forming process for the production of high-quality, rotationally-symmetric, hollow engineering components as widely utilised by the aerospace, automotive and oil & gas sectors. In ICFF, a cylindrical preform is attached to a rotating mandrel and axially-translating rollers apply compression to the outer surface. This leads to extrusion of the workpiece material via significant plastic deformation. As a result of the incremental process - rollers are in contact with a small area of the exterior surface of the workpiece at any one time - the extrusion of the material occurs with significantly lower force than required for conventional forming processes. ICFF is thus well suited to high-strength, hard-to-deform materials. The process is "cold" as a coolant is applied where contact occurs between the workpiece and the roller. The deformation occurs significantly below the material's recrystallisation temperature. As a result, cold work hardening occurs leading to increased strength, stiffness and hardness of the final product. A significant advantage of ICFF over conventional forging and deep drawing is the flexibility it gives engineers to design complex components of varying size. ICFF can result in considerable cost savings via improved yields, reduced production times and improved material properties, as compared to standard manufacturing routes. Furthermore, ICFF allows for rapid prototyping to support virtual product design, thereby reducing development cost and driving innovation.Despite the significant advantages that ICFF has over conventional methods, considerable challenges remain. These must be overcome prior to its widespread adoption. Foremost is the unsatisfactory repeatability and reliability of the process; it can be unstable and failure of the material can occur. Controlling the complex ICFF process is challenging. This is compounded by the large number of process parameters and the highly nonlinear nature of the deformation. Critically, there is currently no accurate and robust model to elucidate the fundamental physical mechanisms that occur during ICFF. Without such a model, the application of ICFF to new products and materials will require costly trial-and-error component-scale testing and remain an art as opposed to a science. The primary aim of this collaborative research proposal between the Advanced Forming Research Centre (AFRC) and the Glasgow Computational Engineering Centre (GCEC) is to develop an engineering design framework to model ICFF. Understanding the response of materials to the loading regime imposed by ICFF is a key component of the model development. To this end, we will undertake a detailed materials characterisation study at the AFRC. The loading on the workpiece will be measured using a highly-instrumented, research-dedicated ICFF machine. In addition, a materials characterisation procedure for ICFF will be developed that will allow industry to test new materials for ICFF thereby reducing the need for costly ICFF trials.The computational model will build upon and significantly extend the existing framework provided by MoFEM - a state-of-the-art, general purpose finite element library developed within the GCEC. The model will account for all key features of ICFF, including significant deformations, contact between rotating parts, thermal effects and residual stresses. The highly non-linear and coupled nature of these processes makes modelling challenging. The modular nature of MoFEM allows us to focus on designing new, efficient and robust numerical methods for ICFF rather than developing the core of the library. The ability of the model to accurately simulate a range of ICFF applications will be demonstrated using component scale testing conducted at the AFRC. Finally the predictive capabilities of the model will be assessed by numerically optimising the process parameters to achieve a desired net shape.
增量冷流成形(ICFF)是一种金属成形工艺,用于生产高质量,旋转对称,空心工程部件,广泛用于航空航天,汽车和石油和天然气行业。在ICFF中,圆柱形预成型件附接到旋转心轴,并且轴向平移辊对外表面施加压缩。这导致工件材料通过显著的塑性变形而被挤出。作为增量工艺的结果-辊在任何一个时间与工件的外表面的小区域接触-材料的挤出以比传统成形工艺所需的显著更低的力发生。因此,ICFF非常适合于高强度、难以变形的材料。该过程是“冷”的,因为冷却剂被施加在工件和辊之间发生接触的地方。变形发生明显低于材料的再结晶温度。结果,发生冷加工硬化,导致最终产品的强度、刚度和硬度增加。ICFF相对于传统锻造和拉深的一个显著优势是它为工程师设计不同尺寸的复杂部件提供了灵活性。与标准制造路线相比,ICFF可以通过提高产量、减少生产时间和改善材料性能来节省大量成本。此外,ICFF允许快速原型,以支持虚拟产品设计,从而降低开发成本和推动创新。尽管ICFF具有显着的优势,传统的方法,相当大的挑战仍然存在。在广泛采用之前,必须克服这些问题。最重要的是工艺的可重复性和可靠性不令人满意;它可能不稳定,并且可能发生材料失效。控制复杂的ICFF过程是具有挑战性的。大量的工艺参数和变形的高度非线性性质加剧了这一问题。关键是,目前还没有准确和可靠的模型来阐明ICFF期间发生的基本物理机制。如果没有这样的模型,ICFF在新产品和新材料中的应用将需要昂贵的试错组件规模测试,并且仍然是一门艺术而不是科学。先进成形研究中心(AFRC)和格拉斯哥计算工程中心(GCEC)之间的这项合作研究提案的主要目的是开发一个工程设计框架来模拟ICFF。了解材料对ICFF施加的加载机制的响应是模型开发的关键组成部分。为此,我们将在武革委进行详细的材料特性研究。工件上的载荷将使用高度仪表化的研究专用ICFF机器进行测量。此外,还将开发ICFF的材料表征程序,这将使工业界能够测试ICFF的新材料,从而减少昂贵的ICFF试验的需要。计算模型将建立在MoFEM提供的现有框架基础上,并显着扩展MoFEM-GCEC内开发的最先进的通用有限元库。该模型将考虑ICFF的所有关键特征,包括显著变形、旋转部件之间的接触、热效应和残余应力。这些过程的高度非线性和耦合性质使得建模具有挑战性。MoFEM的模块化性质使我们能够专注于为ICFF设计新的,高效的和强大的数值方法,而不是开发库的核心。该模型准确模拟一系列ICFF应用的能力将通过在AFRC进行的组件规模测试来证明。最后,该模型的预测能力将通过数值优化的过程参数,以实现所需的净形状进行评估。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Multifield finite strain plasticity: Theory and numerics
多场有限应变塑性:理论和数值
- DOI:10.1016/j.cma.2023.116101
- 发表时间:2023
- 期刊:
- 影响因子:7.2
- 作者:Lewandowski K
- 通讯作者:Lewandowski K
The role of shear dynamics in biofilm formation.
剪切动力学在生物膜形成中的作用。
- DOI:10.1038/s41522-022-00300-4
- 发表时间:2022-04-29
- 期刊:
- 影响因子:9.2
- 作者:Tsagkari, Erifyli;Connelly, Stephanie;Liu, Zhaowei;McBride, Andrew;Sloan, William T.
- 通讯作者:Sloan, William T.
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Chris Pearce其他文献
An Architecture for Flexibly Interleaving Planning and Execution
灵活交错规划和执行的架构
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Yu Bai;Chris Pearce - 通讯作者:
Chris Pearce
Convolutional Neural Networks and the Analysis of Cancer Imagery
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Chris Pearce - 通讯作者:
Chris Pearce
Variations on a Theory of Problem Solving
问题解决理论的变体
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
P. Langley;Chris Pearce;Yunru Bai;Charlotte Worsfold;Mike Barley - 通讯作者:
Mike Barley
Sequoia Sourcing - Deriving a Technology Strategy
- DOI:
10.1016/s1474-6670(17)36859-3 - 发表时间:
2000-09-01 - 期刊:
- 影响因子:
- 作者:
Chris Pearce - 通讯作者:
Chris Pearce
Chris Pearce的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Chris Pearce', 18)}}的其他基金
University of Glasgow ESRC IAA 2023 - 2028
格拉斯哥大学 ESRC IAA 2023 - 2028
- 批准号:
ES/X004414/1 - 财政年份:2023
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
University of Glasgow - Cross-disciplinary research for Discovery Science
格拉斯哥大学 - 发现科学的跨学科研究
- 批准号:
NE/X018296/1 - 财政年份:2022
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
BBSRC IAA University of Glasgow
BBSRC IAA 格拉斯哥大学
- 批准号:
BB/X511110/1 - 财政年份:2022
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
Strategic Support Package: Engineering of Active Materials by Multiscale/Multiphysics Computational Mechanics
战略支持包:通过多尺度/多物理计算力学进行活性材料工程
- 批准号:
EP/R008531/1 - 财政年份:2018
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
Mathematic modelling and computational methods in solid mechanics
固体力学数学建模与计算方法
- 批准号:
EP/E504876/1 - 财政年份:2007
- 资助金额:
$ 157.15万 - 项目类别:
Training Grant
Computational homogenisation for modelling heterogeneous multi-phase materials
用于建模异质多相材料的计算均质化
- 批准号:
EP/D500273/1 - 财政年份:2006
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
相似国自然基金
Improving modelling of compact binary evolution.
- 批准号:10903001
- 批准年份:2009
- 资助金额:20.0 万元
- 项目类别:青年科学基金项目
相似海外基金
Macroeconomic and Financial Modelling in an Era of Extremes
极端时代的宏观经济和金融模型
- 批准号:
DP240101009 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Discovery Projects
Population genomic methods for modelling bacterial pathogen evolution
用于模拟细菌病原体进化的群体基因组方法
- 批准号:
DE240100316 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Discovery Early Career Researcher Award
Anti-infective therapeutics and predictive modelling to tackle Staphylococcus aureus disease
应对金黄色葡萄球菌疾病的抗感染疗法和预测模型
- 批准号:
EP/X022935/2 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Fellowship
Hybrid AI and multiscale physical modelling for optimal urban decarbonisation combating climate change
混合人工智能和多尺度物理建模,实现应对气候变化的最佳城市脱碳
- 批准号:
EP/X029093/1 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Fellowship
Mechanistic Multiscale Modelling Of Drug Release from Immediate Release Tablets
速释片剂药物释放的机制多尺度建模
- 批准号:
EP/X032019/1 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
PIDD-MSK: Physics-Informed Data-Driven Musculoskeletal Modelling
PIDD-MSK:物理信息数据驱动的肌肉骨骼建模
- 批准号:
EP/Y027930/1 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Fellowship
UQ4FM: Uncertainty Quantification for Flood Modelling
UQ4FM:洪水建模的不确定性量化
- 批准号:
EP/Y000145/1 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Research Grant
Advanced Modelling Platform with Moving Ventricular Walls for Increasing Speed to Market of Heart Pumps
具有移动心室壁的先进建模平台可加快心脏泵的上市速度
- 批准号:
10071797 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Collaborative R&D
M2DESCO - Computational Multimode Modelling Enabled Design of Safe & Sustainable Multi-Component High-Entropy Coatings
M2DESCO - 计算多模式建模支持安全设计
- 批准号:
10096988 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
EU-Funded
SMILE - Semantic Modelling of Intent through Large-language Evaluations
SMILE - 通过大语言评估进行意图语义建模
- 批准号:
10097766 - 财政年份:2024
- 资助金额:
$ 157.15万 - 项目类别:
Collaborative R&D